1. Field of the Invention
The present invention concerns a method to correct distortions in image data in a diffusion imaging, and a magnetic resonance system for this purpose. The invention in particular concerns the correction of distortions in the image data that depend on a diffusion weighting and/or diffusion direction in the acquisition of the image data.
2. Description of the Prior Art
Diffusion-weighted magnetic resonance (MR) image data can provide diagnostic information that is important in the clinical routine, for example in stroke and tumor diagnostics. In diffusion-weighted imaging (DWI), diffusion gradients are switched (activated) in specific directions, and the diffusion of water molecules along the applied diffusion gradients attenuates the measured magnetic resonance signal. In areas with lower diffusion, a lesser signal attenuation therefore occurs, such that these regions are imaged with higher image intensity in an imaging magnetic resonance tomography (MRT) measurement. The strength of the diffusion weighting is thereby correlated with the strength of the applied diffusion gradients. The diffusion weighting can be characterized with what is known as the b-value, which is a function of gradient parameters (for example the gradient strength, duration or the interval between the applied diffusion gradients). The acquisition of the resulting magnetic resonance signals ensues with a readout sequence, for example an echoplanar imaging sequence (EPI).
It is essentially the signal-to-noise ratio (SNR) and geometric distortions that are significant for the quality of acquired, diffusion-weighted image data. The time sequence of the switched diffusion gradient pulses can thereby cause dynamic distortions, for example due to eddy current effects. Every activation and deactivation of field gradients can induce such eddy currents, which partially decay with relatively long time constants. Upon readout—i.e. upon measurement of the magnetic resonance signals—corresponding field portions can remain, such that distortions result in the acquired image data. In particular in diffusion-weighted EPI imaging, distortions due to eddy currents represent a significant challenge since here high gradient amplitudes are used in combination with a high sensitivity (for example approximately 10 Hz/image element in the phase coding direction in EPI imaging).
In diffusion imaging, multiple images with different diffusion directions and weightings (characterized by the b-value) are normally acquired and combined with one another in order to calculate parameter maps (Apparent Diffusion Coefficient ADC, Fractional Anisotropy FA), for example. The image distortions caused by the diffusion gradients thereby depend both on the amplitude of the gradients (diffusion weighting) and on their direction (diffusion gradient direction). Given a combination of corresponding individual images, the different distortions for each image lead to incorrect associations of image element information, and therefore to errors or at least to a reduced precision in the calculation of parameters. The distortions can be described as simple affine transformations. The problem is thus created to determine the corresponding transformations to compensate for these distortions. The determination is hindered in that—among other things—the image contrast changes with the varying diffusion weightings and diffusion gradient directions.
To reduce the distortions, the method described in Haselgrove et al., MRM 36:960, 1996 is known in which a b=0 image is acquired as an undistorted reference and an additional image is acquired with a slight diffusion weighting (for example b=150 s/mm2) for every direction to be corrected. Assuming that the distortion effects scale linearly with the amplitude of the generated diffusion gradients, the distortion parameters are thereby determined using an extrapolation. The actual diffusion-weighted images are corrected with this (for example b=1000 s/mm2). However, in this method an adjustment measurement is necessary for every diffusion gradient direction. The determination of the distortion parameters ensues via registration of the image data of the adjustment measurement and the reference measurement. However, the corresponding image data possess only a similar—not identical—contrast, which leads to a lacking robustness of the method, in particular if tissue with rapidly diffusing water molecules (for example spinal fluid or eyeballs) is present in the mapped image segment. Errors in the registration of the image with slight diffusion weighting are furthermore intensified by the extrapolation. In these slightly weighted images distortion are also not strongly expressed, such that a precise determination of the distortion parameters is difficult, wherein errors are again intensified by the extrapolation. A movement of the imaged subject between the acquisition of the reference and the adjustment measurement can lead to an incorrect determination of the correction parameters.
Furthermore, from the printed document Bodammer et al., MRM 51:188-193, 2004 a method is known in which two respective images with identical diffusion direction and diffusion weighting but inverted polarity of the diffusion gradients (i.e. opposite diffusion gradient directions) are acquired. The inverted polarity leads to an unmodified diffusion contrast with a simultaneous inversion of the distortions (a compression is made from a stretching, for example). Due to the identical contrast the registration of the images is facilitated; an extrapolation is also unnecessary. However, two images must respectively be acquired for each diffusion direction and for each diffusion weighting. Given high b-values (diffusion weightings), the signal-to-noise ratio (SNR) in the acquired image data can be very low, such that the registration of the image data and the determination of the distortion parameters is difficult and plagued with a greater imprecision. Furthermore, contrast differences due to directed movement—for example flow or polarization—can lead to a lacking robustness of the method. Movements of the imaged subject between the acquisition of the two measurements can moreover lead to an incorrect determination of the correction parameters.